$k$-Forrelation Optimally Separates Quantum and Classical Query Complexity
Abstract
Aaronson and Ambainis (SICOMP `18) showed that any partial function on $N$ bits that can be computed with an advantage $\delta$ over a random guess by making $q$ quantum queries, can also be computed classically with an advantage $\delta/2$ by a randomized decision tree making ${O}_q(N^{1-\frac{1}{2q}}\delta^{-2})$ queries. Moreover, they conjectured the $k$-Forrelation problem -- a partial function that can be computed with $q = \lceil k/2 \rceil$ quantum queries -- to be a suitable candidate for exhibiting such an extremal separation. We prove their conjecture by showing a tight lower bound of $\widetilde{\Omega}(N^{1-1/k})$ for the randomized query complexity of $k$-Forrelation, where the advantage $\delta = 2^{-O(k)}$. By standard amplification arguments, this gives an explicit partial function that exhibits an $O_\epsilon(1)$ vs $\Omega(N^{1-\epsilon})$ separation between bounded-error quantum and randomized query complexities, where $\epsilon>0$ can be made arbitrarily small. Our proof also gives the same bound for the closely related but non-explicit $k$-Rorrelation function introduced by Tal (FOCS `20). Our techniques rely on classical Gaussian tools, in particular, Gaussian interpolation and Gaussian integration by parts, and in fact, give a more general statement. We show that to prove lower bounds for $k$-Forrelation against a family of functions, it suffices to bound the $\ell_1$-weight of the Fourier coefficients between levels $k$ and $(k-1)k$. We also prove new interpolation and integration by parts identities that might be of independent interest in the context of rounding high-dimensional Gaussian vectors.
- Publication:
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arXiv e-prints
- Pub Date:
- August 2020
- DOI:
- 10.48550/arXiv.2008.07003
- arXiv:
- arXiv:2008.07003
- Bibcode:
- 2020arXiv200807003B
- Keywords:
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- Quantum Physics;
- Computer Science - Computational Complexity
- E-Print:
- 40 pages, 2 figures. Change from v1 to v2: Updated figures to fix an Adobe Acrobat specific issue. Change from v0 to v1: Improved the advantage $\delta$ to $2^{-O(k)}$ strengthening the main conclusions. Added a reference to the independent work of Sherstov, Storozhenko and Wu (arxiv:2008.10223) who obtained a similar lower bound for the randomized query complexity of $k$-Rorrelation